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Data Science & AI

Deep Learning with PyTorch

Build, train and deploy neural networks, from tensors to transfer learning.

4.8(980)9.4K students9 lessons · 2h 21m

Last updated 29 Jul 2026, 00:00

Dr. Sanjay Rao · Machine Learning Research Scientist
Nothing is charged in this demo.

About this course

A from-first-principles course in deep learning using PyTorch. You'll write and train networks by hand before reaching for pretrained models, so the architectures in the second half (CNNs, attention, transfer learning) actually make sense.

What you'll learn

  • Build and train neural networks in PyTorch from scratch
  • Understand backpropagation well enough to debug it
  • Apply CNNs and attention-based models to real tasks
  • Use transfer learning to get results with less data
  • Train on GPUs and deploy a trained model

Curriculum

3 sections · 9 lessons · 2h 21m

  • Tensors and autograd in PyTorch14m
  • Building your first neural network17m
  • Backpropagation, intuitively15m

Student reviews

Jordan Casey

17 Jan 2026, 00:00

5.0

This is the course I wish I'd found a year ago. Practical from lesson one.

Ben Sorensen

19 May 2025, 00:00

3.0

The pacing dragged a little in the middle, but the final project pulled it all together.

Ella Vance

10 Sept 2025, 00:00

4.0

Solid course overall, though I'd have liked a couple more advanced examples.